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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
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1. Introduction [Bow99], and the phase controlled microwave heating method was applied in [BPJD99]. According to the results shown in the three papers, although relatively homogeneous EM field distributions can be created using above methods, the resulting temperature distribu- tions were not as uniform as expected, and local hot spots still ex- isted. The other category relies on mechanical approaches that can improve the temperature homogeneity directly. For instance, the method in [WRK+12] used the real experimental results to adjust the position of a susceptor, in order to achieve a specified heating at particular areas. Anotherexampleisthehybridsystemusedin[KHYM13]thatconsists of both the microwave and hot air heatings, to get a enhanced surface heatingandreducethetemperaturegradientbetweenthesurfaceand core of the product. These approaches are intuitive and effective. But on the other hand, they are either too difficult or not efficient enough tobeextendedtomoregeneral cases. Despite numerous approaches were applied, no systematical solution has been established to solve the problem of the temperature non- uniformity in microwave heating. So far it still remains as one of the mostchallengingproblemsinmicrowaveheating. 1.3. Objectiveandcontent In this dissertation, a novel adaptive temperature control concept for microwave heating is proposed, which combines the distributed microwave feeding system with advanced multiple-input multiple- output (MIMO) control methods. The idea of distributed microwave feeding systems was presented and proved to be effective in [Feh09]. Based on this theory, HEPHAISTOS, which is short for high elec- tromagnetic power heated automated injected structure oven system [Feh09], was designed. HEPHAISTOS has more than one microwave feedingsourcesandaveryuniquehexagonalstructuredcavityshape, resulting in a rather homogeneous EM field distribution in the whole cavity scale [Feh09]. More important, the EM field distribution in HEPHAISTOS can be changed during the heating process, by adjust- ing the power of individual heating sources, to achieve better tem- 10
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Title
Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
Author
Yiming Sun
Publisher
KIT Scientific Publishing
Location
Karlsruhe
Date
2016
Language
English
License
CC BY-SA 3.0
ISBN
978-3-7315-0467-2
Size
14.8 x 21.0 cm
Pages
260
Keywords
Mikrowellenerwärmung, Mehrgrößenregelung, Modellprädiktive Regelung, Künstliches neuronales Netz, Bestärkendes Lernenmicrowave heating, multiple-input multiple-output (MIMO), model predictive control (MPC), neural network, reinforcement learning
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Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources